(a) Field of the Invention
The present invention relates to a method of calculating a soft value and a method of detecting a transmission signal. More particularly, the present invention relates to a method of calculating a soft value and a method of detecting a transmission signal in a multiple input multiple output (MIMO) system using spatial multiplexing (SM).
(b) Description of the Related Art
The next generation mobile communication system has been required to provide high-rate data transmission for stationary and mobile environments. In order to satisfy these requirements, a multiple input multiple output (MIMO) system using spatial multiplexing (SM) that enables high-rate data transmission by enabling multiple data stream transmission has attracted attention.
In the MIMO system using spatial multiplexing, a transmitting terminal transmits data streams indicating different information through each transmitting antenna and a receiving terminal separates the data streams transmitted from the transmitting terminal.
In the data layer separation method according to the related art, maximum likelihood (ML) bit metric detection has been used in which a maximum likelihood metric is calculated for each of signal vectors that can be transmitted and a transmission signal vector having the smallest ML metric is searched, in order to perform optimal transmission signal detection.
However, while the ML bit metric detection provides optimal transmission signal detection performance, it has a drawback in that extremely high complexity is required, because hardware complexity is exponentially increased with respect to the size of a constellation and the number of transmitting antennas.
In order to complement the drawback in the ML bit metric detection, as linear signal detection having reduced complexity, a zero forcing (ZF) method and a minimum mean square estimator (MMSE) method have been suggested in the related art. However, these methods have a problem in that performance is degraded as compared with the ML bit metric detection. Further, in order to complement the drawback in the ML bit metric detection, as non-linear signal detection having reduced complexity, ordered successive interference cancellation (OSIC) that is known as vertical Bell Lab layered space time (VBLAST) has been suggested. However, while the VBLAST can be easily implemented and provides excellent performance than the ZF and MMSE methods, it has a problem in that performance is degraded as compared with the ML bit metric detection.
The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.